class_docstr: Split the dataset into `num_parts` parts and sample from the part with index `part_index`
  
  Parameters
  ----------
  length: int
    Number of examples in the dataset
  num_parts: int
    Partition the data into multiple parts
  part_index: int
    The index of the part to read from
class_docstr_tok: ["Split","the","dataset","into","`","num_parts","`","parts","and","sample","from","the","part","with","index","`","part_index","`","Parameters","--","--","--","--","--","length",":","int","Number","of","examples","in","the","dataset","num_parts",":","int","Partition","the","data","into","multiple","parts","part_index",":","int","The","index","of","the","part","to","read","from"]
code: def __len__(self):
      return self.part_len
  
file_path: gluon-cv/gluoncv/data/sampler.py
imports: import random
  import numpy
  from mxnet import gluon
label_desc: Use image node_id 3 for calling the SplitSampler obj's underlying member method code with example usage: obj.__len__() and returns: self